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Start from the painful failure mode, not from the model
Select one asset, one failure pattern, and one concrete consequence: unplanned downtime, scrap, or rework. If the initiative begins with 'we want AI for maintenance' without narrowing the event to anticipate, the plant will only receive more signals with no linked decision.
Stabilize signals, windows, and thresholds before enrichment
IoT without signal hygiene only creates false urgency. First confirm capture frequency, acceptable lag, units, reliable sensors, and thresholds a technician already recognizes as useful. Then add RAG to explain why the alert matters and what to do next.
- Review historical signal quality and blind periods.
- Define one operating threshold and one observation threshold.
- Align every alert to a first-response owner.
Connect the alert to manuals, previous failures, and shift notes
RAG adds value when the alert no longer arrives alone. It should retrieve manuals, previous tickets, safety checklists, and field notes so the technician knows what to inspect first and what mistake not to repeat.
Design a short, repeatable triage
Do not give the team a long answer. Give them a triage: severity, main hypothesis, sources reviewed, and recommended first action. If the operator has to reinterpret a wall of text before acting, the system is not ready for production.
Close the loop with escalation, discard, and learning
Every alert must end labeled as valid, false, or insufficient. That outcome feeds threshold tuning, document curation, and the decision to instrument the asset better. Without that closure, the playbook degrades in weeks.
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